THE POTENTIAL OF LIGHT LASER SCANNERS DEVELOPED FOR UNMANNED AERIAL VEHICLES – THE REVIEW AND ACCURACY

31 citations as recorded by crossref.

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7. Individual Tree Canopy Parameters Estimation Using UAV-Based Photogrammetric and LiDAR Point Clouds in an Urban Park E. Ghanbari Parmehr & M. Amati https://doi.org/10.3390/rs13112062
8. Investigating Practical Impacts of Using Single-Antenna and Dual-Antenna GNSS/INS Sensors in UAS-Lidar Applications R. Brazeal et al. https://doi.org/10.3390/s21165382
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12. Low-Cost iOS-Based Automated Detection of Under-Construction Interior Drywalls: An Exploratory Study Y. Zhang et al. https://doi.org/10.1061/JCEMD4.COENG-16417
13. Quantitative Comparison of UAS-Borne LiDAR Systems for High-Resolution Forested Wetland Mapping N. Pricope et al. https://doi.org/10.3390/s20164453
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15. Improving Chinese Fir Plantations DBH Inversion Accuracy Using Ensemble Learning Models Base on UAV-LiDAR J. Xu et al. https://doi.org/10.1109/JSTARS.2025.3560704
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18. Machine Learning for Precise Rice Variety Classification in Tropical Environments Using UAV-Based Multispectral Sensing A. Wijayanto et al. https://doi.org/10.3390/agriengineering5040123
19. The Lidargrammetric Model Deformation Method for Altimetric UAV-ALS Data Enhancement A. Rzonca & M. Twardowski https://doi.org/10.3390/rs14246391
20. Scan Pattern Characterization of Velodyne VLP-16 Lidar Sensor for UAS Laser Scanning H. Lassiter et al. https://doi.org/10.3390/s20247351
21. Using Drones for Dendrometric Estimations in Forests: A Bibliometric Analysis B. Silva et al. https://doi.org/10.3390/f15111993
22. Comparability of multi‐temporal DTMs derived from different LiDAR platforms: Error sources and uncertainties in the application of geomorphic impact studies N. Kamp et al. https://doi.org/10.1002/esp.5540
23. Estimation of Sugarcane Yield Using a Machine Learning Approach Based on UAV-LiDAR Data J. Xu et al. https://doi.org/10.3390/rs12172823
24. Accuracy Assessment of Point Clouds from LiDAR and Dense Image Matching Acquired Using the UAV Platform for DTM Creation A. Salach et al. https://doi.org/10.3390/ijgi7090342
25. UAV LiDAR surveys and machine learning improve snow depth and water equivalent estimates in boreal landscapes M. Ylönen et al. https://doi.org/10.5194/tc-19-4585-2025
26. Quality Analysis of Direct Georeferencing in Aspects of Absolute Accuracy and Precision for a UAV-Based Laser Scanning System A. Dreier et al. https://doi.org/10.3390/rs13183564
27. Exploring the Potential of UAV LiDAR Data for Trunk Point Extraction and Direct DBH Measurement B. Feng et al. https://doi.org/10.3390/rs14122753
28. Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study L. Pereira et al. https://doi.org/10.3390/rs13030419
29. Demonstration of a compact double-reflection transmissive beam scanner operating at 1550  nm wavelength J. Baker et al. https://doi.org/10.1364/AO.514908
30. Single-Pass UAV-Borne GatorEye LiDAR Sampling as a Rapid Assessment Method for Surveying Forest Structure G. Prata et al. https://doi.org/10.3390/rs12244111
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